Verify This Week (2/2016)
Here, we provide interesting links from around the web that discuss issues regarding the verification of content from social media: what tools, services and initiatives are there? Who is doing what? What’s the state of affairs regarding eyewitness media and related issues? Here is our list for this week.
France 24 Observer’s “Debunked” segment
France 24 Observer publishes videos in their “Debunked” segment on YouTube. In one of their videos, they show how people use old pictures and claim them to be news.
“[…] we take a look at some of the most incendiary images making the rounds online, and check to see that they really are what they say they are. Watch out, because Internet users have a habit of recycling old pictures – and using them for their own agenda.”
Source: France 24 Observer
New EC co-funded project InVID focuses on video verification
This week, EC co-funded project InVID kicked off with a consortium meeting discussing legal issues, requirements and the technical frameworks. InVID has a specific focus on video verification of eyewitness media <Disclaimer: REVEAL’s partner Deutsche Welle and this website’s authors Jochen Spangenberg and Ruben Bouwmeester are also part of InVID’s consortium> and we are looking forward to seeing more in the upcoming weeks and months.
Visual clues for verification
This article is a great tutorial for understanding visual clues in images and videos that are necessary for verifying content. There are many visual clues that might be helpful, such as clothing, landscape, weather or cars. For a full list, check out this article.
This video is just one example of how journalists could work their way through verifying an image:
Source: First Draft News
If you have not heard about Verified Pixel, this article written by Alastair Reid, Managing Editor of First Draft News, is very informative:
“Verified Pixel conducts a number of checks on any new image added to its database: checking Google Images and TinEye to see if and when the picture has appeared online before; scanning the image file for EXIF data to understand when, where and on what device it was captured; and running it through image forensics tool Izitru to see if the image has been altered.”